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(H2, NH3). The successful candidate will leverage high-performance computing (HPC) resources at the Laboratory to perform CFD simulations of low-carbon fuel injection, mixing, combustion, and emissions
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be to develop high fidelity simulations and/or algorithms to enable Bragg coherent diDraction imaging. We expect x-ray ptychography and coded aperture methods to play a fundamental role in creating a
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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simulation laboratory as well as supporting ongoing DOE projects. Candidates will be required to work in at least 4 of the following areas: Develop a functioning test bed using Opal-RT PHIL real-time platform
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the goal to enhance predictive capability and scalability of multi-scale and multi-physics simulation codes. The prospective postdoctoral appointee will perform multi-physics and multi-scale CFD simulations
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microscope, as well as electrostatic beam blanker or ultrafast pulser in electron microscopes. Proficient in data analysis and modeling, with experience using Python and other programming or simulation tools
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oscillators driven by the storage-ring RF signals to fulfill the function of manipulating X-ray pulses. More specific responsibilities include MEMS design and simulation, testing and characterization
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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Lab. Research at CPAC covers theory, modeling
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to solve challenging problems in the microelectronics area. Note: Synthesis of bulk materials, first-principles simulations/modeling, and organic or bio-related areas are not in consideration
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computer science or related computational engineering disciplines. Experience with simulation frameworks for complex computer systems and architectures. Some knowledge of accelerator (CUDA, SYCL, HIP) and scientific